Pune, India -- (SBWIRE) -- 07/21/2018 -- Artificial Intelligence (AI) in agriculture is utilization of cognitive technologies that helps in learning, reasoning, understanding and interacting, which in result increases the efficiency. It offers various advantages such as Image recognition and insight, chatbots for farmers, help IoT achieve its maximum potential and determine the best options to maximize return on crops.

Market Analysis:

The Global AI in Agriculture Market accounted for USD 432.5 million in 2017 and is projected to grow at a CAGR of 22.7% during the forecast period of 2018 to 2025. The upcoming market report contains data for historic years 2014, 2015, the base year of calculation is 2017 and the forecast period is 2018 to 2025.

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Global AI in Agriculture Market By Offering (Hardware, Software, Service, AI-As-A-Service), By Technology (Predictive Analytics, Machine Learning, Computer Vision), By Application (Livestock Monitoring, Precision Farming, Agriculture Robots, Livestock Monitoring, Drone Analytics), By Geography (North America, Europe, Asia-Pacific, Europe, South America, Middle East and Africa) Industry Trends and Forecast to 2025

Top Key Competitors:

- IBM
- Microsoft Corporation
- Descartes Labs
- Deere & Company
- Granular
- aWhere
- The Climate Corporation
- Agribotix LLC
- Tule Technologies
- Prospera
- Mavrx Inc.
- Cropx
- Harvest Croo
- Farmbot
- Trace Genomics
- Spensa Technologies Inc.
- Resson
- Vision Robotics
- Autonomous Tractor Corporation
- Among others.

Major Market Drivers:

- Increasing adoption of new advanced technologies and IMS
- Rising demand for agricultural production
- Government support and initiatives for the adoption of modern agricultural techniques
- Maximizing crop productivity along with the implementation of various techniques
- Increasing use of drones in agricultural farms

Market Restraint:

- High Cost involved during precise field data collection.

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Market Segmentation:

On the basis of offering, the global AI in agriculture market is segmented into hardware, software, service, AI-As-A-Service. Hardware is sub segmented into network, storage device and processor. Software is sub segmented into AI Platform and AI Solution. Service is sub segmented into support and maintenance and deployment and integration.

On the basis of technology, the global AI in agriculture market is segmented into predictive analytics, machine learning and computer vision.

On the basis of application, the global AI in agriculture market is segmented into livestock monitoring, precision farming, agriculture robots, livestock monitoring, drone analytics and others. Precision farming is sub segmented into yield monitoring, crop scouting, weather tracking and forecasting, field mapping and irrigation management. Others are sub segmented into smart greenhouse applications, fish farming application and soil management. Soil Management is further sub segmented into nutrient monitoring and moisture monitoring.

On the basis of geography, the global AI in agriculture market report covers data points for 28 countries across multiple geographies such as North America, South America, Europe, Asia-Pacific and Middle East & Africa. Some of the major countries covered in this report are U.S., Canada, Germany, France, U.K., Netherlands, Switzerland, Turkey, Russia, China, India, South Korea, Japan, Australia, Singapore, Saudi Arabia, South Africa, and Brazil among others.

Reason to Buy

- Save and reduce time carrying out entry-level research by identifying the growth, size, leading players and segments in the Global AI in Agriculture Market.

- Highlights key business priorities in order to assist companies to realign their business strategies.

- The key findings and recommendations highlight crucial progressive industry trends in the Global AI in Agriculture Market, thereby allowing players to develop effective long term strategies.

- Develop/modify business expansion plans by using substantial growth offering developed and emerging markets.

- Scrutinize in-depth global market trends and outlook coupled with the factors driving the market, as well as those hindering it.

- Enhance the decision-making process by understanding the strategies that underpin commercial interest with respect to products, segmentation and industry verticals.

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